التفاصيل البيبلوغرافية
| العنوان: |
Bilingual lexicon induction across orthographically-distinct under-resourced Dravidian languages |
| المؤلفون: |
Chakravarthi, Bharathi Raja, Rajasekaran, Navaneethan, Arcan, Mihael, McGuinness, Kevin, O'Connor, Noel E., McCrae, John P. |
| المصدر: |
Chakravarthi, Bharathi Raja orcid:0000-0002-4575-7934 , Rajasekaran, Navaneethan, Arcan, Mihael orcid:0000-0002-3116-621X , McGuinness, Kevin orcid:0000-0003-1336-6477 , O'Connor, Noel E. orcid:0000-0002-4033-9135 and McCrae, John P. orcid:0000-0002-7227-1331 (2020) Bilingual lexicon induction across orthographically-distinct under-resourced Dravidian languages. In: 7th Workshop on NLP for Similar Languages, Varieties and Dialects, 13 Dec 2020, Barcelona, Spain (Online). |
| بيانات النشر: |
International Committee on Computational Linguistics (ICCL) |
| سنة النشر: |
2020 |
| المجموعة: |
Dublin City University: DCU Online Research Access Service (DORAS) |
| مصطلحات موضوعية: |
Computational linguistics, Information retrieval, Machine translating |
| الوصف: |
Bilingual lexicons are a vital tool for under-resourced languages and recent state-of-the-art approaches to this leverage pretrained monolingual word embeddings using supervised or semi- supervised approaches. However, these approaches require cross-lingual information such as seed dictionaries to train the model and find a linear transformation between the word embedding spaces. Especially in the case of low-resourced languages, seed dictionaries are not readily available, and as such, these methods produce extremely weak results on these languages. In this work, we focus on the Dravidian languages, namely Tamil, Telugu, Kannada, and Malayalam, which are even more challenging as they are written in unique scripts. To take advantage of orthographic information and cognates in these languages, we bring the related languages into a single script. Previous approaches have used linguistically sub-optimal measures such as the Levenshtein edit distance to detect cognates, whereby we demonstrate that the longest common sub-sequence is linguistically more sound and improves the performance of bilingual lexicon induction. We show that our approach can increase the accuracy of bilingual lexicon induction methods on these languages many times, making bilingual lexicon induction approaches feasible for such under-resourced languages. |
| نوع الوثيقة: |
conference object |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
http://doras.dcu.ie/25223/1/Bilingual%20Lexicon%20Induction%20across%20Orthographically-distinctUnder-Resourced%20Dravidian%20Languages.pdf; https://www.aclweb.org/anthology/2020.vardial-1.6; http://doras.dcu.ie/25223/ |
| الاتاحة: |
http://doras.dcu.ie/25223/ |
| Rights: |
© 2020 The Authors. CC-BY-4.0 |
| رقم الانضمام: |
edsbas.B731B5A4 |
| قاعدة البيانات: |
BASE |